This study proposes a coordination of load frequency control (LFC) and superconducting magnetic energy storage (SMES) technology (i.e. auxiliary LFC) using a new optimal PID controller‐based moth swarm algorithm (MSA) in Egyptian Power System (EPS) considering high wind power penetration (HWPP) (as a future planning of the EPS). This strategy is proposed for compensating the EPS frequency deviation, preventing the conventional generators from exceeding their power ratings during load disturbances, and mitigating the power fluctuations from wind power plants. To prove the effectiveness of the proposed coordinated control strategy, the EPS considering HWPP was tested by the MATLAB/SIMULINK simulation. The convention generation system of the EPS is decomposed into three dynamics subsystems; hydro, reheat and non‐reheat power plants. Moreover, the physical constraints of the governors and turbines such as generation rate constraints of power plants and speed governor dead band (i.e. backlash) are taking into consideration. The results reveal the superior robustness of the proposed coordination against all scenarios of different load profiles, and system uncertainties in the EPS considering HWPP. Moreover, the results have been confirmed by comparing it with both; the optimal LFC with/without the effect of conventional SMES, which without modifying the input control signal.

Multi-area power systems inhere complicated nonlinear response, which results in degraded performance due to the insufficient damping. The main causes of the damping problems are the stochastic behavior of the renewable energy sources, loading conditions, and the variations of system parameters. The load frequency control (LFC) represents an essential element for controlling multi-area power systems. Therefore, the proper design of the controllers is mandatory for preserving reliable, stable and high-quality electrical power. The controller has to suppress the deviations of the area frequency in addition to the tie-line power. Therefore, this paper proposes a new frequency regulation method based on employing the hybrid fractional order controller for the LFC side in coordination with the fractional order proportional integral derivative (FOPID) controller for the superconducting energy storage system (SMES) side. The hybrid controller is designed based on combining the FOPID and the tilt integral derivative (TID) controllers. In addition, the controller parameters are optimized through a new application of the manta ray foraging optimization algorithm (MRFO) for determining the optimum parameters of the LFC system and the SMES controllers. The optimally-designed controllers have operated cooperatively and hence the deviations of the area frequency and tie-line power are efficiently suppressed. The robustness of the proposed controllers is investigated against the variation of the power system parameters in addition to the location and/or magnitude of random/step load disturbances.

Several issues have been risen due to the recent vast installations of renewable energy sources (RESs) instead of fossil fuel sources in addition to the replacement of electric vehicles (EVs) for fuel-powered vehicles. Mitigating frequency deviations and tie-line power fluctuations has become driving challenge for the control design of interconnected power systems. RESs represent continuously varying power generators due to their nature and dependency on the environmental conditions. In this context, this article presents a new modified hybrid fractional order controller for load frequency and EVs control in interconnected power systems. The new controller combines the benefits of two widely employed fractional order controllers, including the FOPID and TID controllers. In addition, a new practical application of recent artificial ecosystem optimization (AEO) method has been proposed in this article for determining simultaneously the optimum controller parameters. The proposed controller and optimization method are validated on two areas interconnected power system with different types of RESs and with considering the natural characteristics of sources, EVs and load variations. Obtained simulation results verify the superior performance of the proposed controller and optimization method for achieving high mitigation of frequency fluctuations and tie-line power deviations, increased robustness, enhanced system stability over a wide range of parameters uncertainty and fast response during transients.

The low system inertia and the high sensitivity to load and generation fluctuations represent the main challenges for future ambitious plans of modern power systems accompanied by high penetrations levels of the renewable energy sources (RESs). Therefore, this paper presents a new approach for solving the load frequency control (LFC) in addition to the virtual inertia control (VIC) in interconnected RESs penetrated power systems using cooperative tilt-based controllers and a hybrid modified particle swarm optimization with genetic algorithm (MPSOGA). The VIC system is adopted using superconducting magnetic energy storage (SMES) to provide sufficient inertial energy for system stability. Two tilt-based controllers are employed in each area using the tilt-integral-derivative (TID) controller for the SMES and TID with filter (TIDF) for the LFC function. The cooperative optimum design of the TID/TIDF controllers leads to the enhancement of frequency stability in studied two-area power systems. The formulated optimization process aims to minimize the frequency nadir settling time during abrupt changes of RESs and/or load changes, considering the cooperative control of LFC and VIC. The proposed approach has been applied to a case study consisting of two-area power systems, connected via hybrid high voltage DC/AC (hybrid HVAC/HVDC) tie-line, integrated with distributed conventional generations, photovoltaic (PV), and wind generation systems. Performance analysis has been conducted to demonstrate the effectiveness of the proposed method is compared to the genetic algorithm (GA) and particle-swarm optimization (PSO) using high fluctuations of renewable generations under extreme changes in loading conditions and physical parameters variation. The obtained results show the superiority of MPSOGA approach on the other competitive optimization techniques.

This paper presents a coordination strategy of Load Frequency Control (LFC) and digital frequency protection for an islanded microgrid (MG) considering high penetration of Renewable Energy Sources (RESs). In such MGs, the reduction in system inertia due to integration of large amount of RESs causes undesirable influence on MG frequency stability, leading to weakening of the MG. Furthermore, sudden load events, and short circuits caused large frequency fluctuations, which threaten the system security and could lead to complete blackouts as well as damages to the system equipment. Therefore, maintaining the dynamic security in MGs is one of the important challenges, which considered in this paper using a specific design and various data conversion stages of a digital over/under frequency relay (OUFR). The proposed relay will cover both under and over frequency conditions in coordination with LFC operation to protect the MG against high frequency variations. To prove the response of the proposed coordination strategy, a small MG was investigated for the simulation. The proposed coordination method has been tested considering load change, high integration of RESs. Moreover, the sensitivity analysis of the presented technique was examined by varying the penetration level of RESs and reducing the system inertia. The results reveal the effectiveness of the proposed coordination to maintain the power system frequency stability and security. In addition, the superiority of the OUFR has been approved in terms of accuracy and speed response during high disturbances.

Fuel cell (FC) represents one of the promising efficient solutions for future energy supply. Improving performance and integration methods of FCs via maximum power point tracking (MPPT) and high boosting factor inverters are key requirements for research in renewable energy fields. Recently, hybrid FC-battery structures have shown wide applications in several areas. Accordingly, marine predators algorithm (MPA) is proposed in this article for optimizing the design of reduced sensor fuzzy-logic based MPPT scheme. The proposed scheme inherits the following benefits: reduced sensors and hence reduced costs, more flexibility and smooth performance due to fuzzy-logic based MPPT, and optimized design method of fuzzy-logic based MPPT through MPA method. Moreover, a high boosting ratio inverter is introduced in this article based on using the switched capacitor multilevel inverter (SCMLI). The proposed system achieves self capacitor voltage control without complex control or extra sensors. The proposed hybrid FC-battery system has been validated at various operating points. In addition, comprehensive comparisons with existing schemes in the literature are provided in the paper. The superiority of the proposed scheme has been verified with robust, fast and accurate tracking, reduced cost, flexible, simple, and smooth output waveforms. The proposed method achieves the lowest output power fluctuations with fast tracking speed compared to the studied classical methods.